Publication list
Also, visit my Scholar page.
2023
A. Pirinen, O. Mogren, M. Västerdal, Fully Convolutional Networks for Dense Water Flow Intensity Prediction in Swedish Catchment Areas, arXiv preprint, arXiv
2022
E. Ekblom, E. Listo Zec, O. Mogren, EFFGAN: Ensembles of fine-tuned federated GANs, 2022 IEEE International Conference on Big Data, 2022 IEEE International Conference on Big Data
J. Martinsson, M. Willbo, A. Pirinen, O. Mogren, M. Sandsten, Few-shot bioacoustic event detection using a prototypical network ensemble with adaptive embedding functions, Detection and Classification of Acoustic Scenes and Events 2022, DCASE 2022
S. Fallahi, A. Mellquist, O. Mogren, E. Listo Zec, L. Hallquist, Financing Solutions for Circular Business Models: Exploring the Role of Business Ecosystems and Artificial Intelligence, Business Strategy and the Environment, Business Strategy and the Environment
J. Martinsson, M. Runefors, H. Frantzich, D. Glebe, M. McNamee, O. Mogren, A Novel Method for Smart Fire Detection Using Acoustic Measurements and Machine Learning: Proof of Concept, Journal of Fire Technology, Fire Technol.
E. Listo Zec, E. Ekblom, M. Willbo, O. Mogren, S. Girdzijauskas, Decentralized adaptive clustering of deep nets is beneficial for client collaboration, International Workshop on Trustworthy Federated Learning 2022, FL-IJCAI'22
2021
J. Martinsson, E. Listo Zec, D. Gillblad, O. Mogren, Adversarial representation learning for synthetic replacement of private attributes, 2021 IEEE International Conference on Big Data, IEEE BigData 2021
N. Onoszko, G. Karlsson, O. Mogren, E. Listo Zec, Decentralized federated learning of deep neural networks on non-iid data, 2021 Workshop on Federated Learning for User Privacy and Data Confidentiality at the 38th International Conference on Machine Learning, FL-ICML 2021
A. Hilmkil, S. Callh, M. Barbieri, L. René Sütfeld, E. Listo Zec, O. Mogren, Scaling Federated Learning for Fine-Tuning of Large Language Models, International Conference on Applications of Natural Language to Information Systems, NLDB 2021
2020
E. Listo Zec, O. Mogren, J. Martinsson, L. René Sütfeld, D. Gillblad, Specialized federated learning using a mixture of experts, Arxiv Preprint 2020, Arxiv 2020
D. Ericsson, A. Östberg, E. Listo Zec, J. Martinsson, O. Mogren, Adversarial representation learning for private speech generation, The Workshop on Self-supervision in Audio and Speech at the 37th International Conference on Machine Learning, ICML-SAS 2020
2019
J. Martinsson, A. Schliep, B. Eliasson, O. Mogren, Blood glucose prediction with variance estimation using recurrent neural networks, Journal of Healthcare Informatics Research, JHIR
E. Listo Zec, O. Mogren, Grammatical gender in Swedish is predictable using recurrent neural networks, SweCog 2019, SweCog 2019
J. Martinsson, O. Mogren, Semantic segmentation of fashion images using feature pyramid networks, Second Workshop on Computer Vision for Fashion, Art and Design at ICCV 2019, CVCREATIVE 2019
M. Korneliusson, J. Martinsson, O. Mogren, Generative modelling of semantic segmentation data in the fashion domain, Second Workshop on Computer Vision for Fashion, Art and Design at ICCV 2019, CVCREATIVE 2019
O. Mogren, R. Johansson, Character-based recurrent neural networks for morphological relational reasoning, Journal of language modelling, JLM 2019
2017
M. Kågebäck, O. Mogren, Disentanglement by Penalizing Correlation, NIPS Workshop on Learning Disentangled Features: from Perception to Control 2017, DisentangleNIPS 2017
O. Mogren, R. Johansson, Character-based recurrent neural networks for morphological relational reasoning, Subword & Character Level Models in NLP (SCLeM) workshop at EMNLP 2017 in Copenhagen, Denmark, September 7., SCLeM 2017
2016
S. Almgren, S. Pavlov, O. Mogren, Named entity recognition in Swedish health records with character-based deep bidirectional LSTMs, Fifth workshop on building and evaluating resources for biomedical text mining (BioTxtM 2016) at COLING 2016 in Osaka, December 12., BioTxtM 2016
O. Mogren, C-RNN-GAN: Continuous recurrent neural networks with adversarial training, Constructive Machine Learning Workshop (CML) at NIPS 2016 in Barcelona, Spain, December 10., CML 2016
J. Hagstedt P Suorra, O. Mogren, Assisting discussion forum users using deep recurrent neural networks, Representation learning for NLP, RepL4NLP at ACL 2016 in Berlin, August 11., RepL4NLP 2016
2015 and earlier
O. Mogren, M. Kågebäck, D. Dubhashi, Extractive summarization by aggregating multiple similarities, RANLP 2015, Hissar, Bulgaria, September 6th-11th, RANLP 2015
N. Tahmasebi, L. Borin, G. Capannini, D. Dubhashi, P. Exner, M. Forsberg, G. Gossen, F. D. Johansson, R. Johansson, M. Kågebäck, O. Mogren, P. Nugues, T. Risse, Visions and open challenges for a knowledge-based culturomics, International Journal on Digital Libraries, February 2015, IJDL 2015
P. Damaschke, O. Mogren, Editing simple graphs, Journal of Graph Algorithms and Applications 18 (2014), JGAA 2014
M. Kågebäck, O. Mogren, N. Tahmasebi, D. Dubhashi, Extractive summarization using continuous vector space models, 2nd Workshop on Continuous Vector Space Models and their Compositionality CVSC 2014, Gothenburg Sweden, CVSC 2014
O. Mogren, O. Sandberg, V. Verendel, D. Dubhashi, Adaptive dynamics of realistic small-world networks, European Conference on Complex Systems 2009, ECCS 2009